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ICASSP
2010
IEEE
15 years 7 months ago
Learning sparse systems at sub-Nyquist rates: A frequency-domain approach
We propose a novel algorithm for sparse system identification in the frequency domain. Key to our result is the observation that the Fourier transform of the sparse impulse respo...
Martin McCormick, Yue M. Lu, Martin Vetterli
170
Voted
CORR
2010
Springer
146views Education» more  CORR 2010»
15 years 7 months ago
Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
Daniel Golovin, Andreas Krause
TCSV
2008
174views more  TCSV 2008»
15 years 6 months ago
A Survey of Vision-Based Trajectory Learning and Analysis for Surveillance
Abstract--This paper presents a survey of trajectory-based activity analysis for visual surveillance. It describes techniques that use trajectory data to define a general set of ac...
Brendan Tran Morris, Mohan M. Trivedi
IVC
2007
184views more  IVC 2007»
15 years 6 months ago
Image distance functions for manifold learning
Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. When the image data set is not a linear combination of a small number of bas...
Richard Souvenir, Robert Pless
TNN
2008
82views more  TNN 2008»
15 years 6 months ago
Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks
In this paper, a general method for the numerical solution of maximum-likelihood estimation (MLE) problems is presented; it adopts the deterministic learning (DL) approach to find ...
Cristiano Cervellera, Danilo Macciò, Marco ...